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Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration
February 2012 (vol. 34 no. 2)
pp. 315-327
ASCII Text
x 
 
S. Alpert, M. Galun, A. Brandt, R. Basri, "Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 2, pp. 315-327, February, 2012.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2011.130,
author = {S. Alpert and M. Galun and A. Brandt and R. Basri},
title = {Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {34},
number = {2},
issn = {0162-8828},
year = {2012},
pages = {315-327},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2011.130},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration
IS - 2
SN - 0162-8828
SP315
EP327
EPD - 315-327
A1 - S. Alpert,
A1 - M. Galun,
A1 - A. Brandt,
A1 - R. Basri,
PY - 2012
KW - image texture
KW - computational complexity
KW - computer vision
KW - graph theory
KW - image segmentation
KW - computer vision
KW - probabilistic bottom-up aggregation
KW - cue integration
KW - pixel merging
KW - texture distributions
KW - texture cues
KW - graph coarsening scheme
KW - hierarchical image segmentation
KW - algorithm complexity
KW - user-tuned parameters
KW - Image segmentation
KW - Computer vision
KW - Algorithm design and analysis
KW - Probabilistic logic
KW - Noise measurement
KW - Partitioning algorithms
KW - Clustering algorithms
KW - segmentation evaluation.
KW - Computer vision
KW - image segmentation
KW - cue integration
VL - 34
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
S. Alpert, Fac. of Math. & Comput. Sci., Weizmann Inst. of Sci., Rehovot, Israel
M. Galun, Fac. of Math. & Comput. Sci., Weizmann Inst. of Sci., Rehovot, Israel
A. Brandt, Fac. of Math. & Comput. Sci., Weizmann Inst. of Sci., Rehovot, Israel
R. Basri, Fac. of Math. & Comput. Sci., Weizmann Inst. of Sci., Rehovot, Israel
We present a bottom-up aggregation approach to image segmentation. Beginning with an image, we execute a sequence of steps in which pixels are gradually merged to produce larger and larger regions. In each step, we consider pairs of adjacent regions and provide a probability measure to assess whether or not they should be included in the same segment. Our probabilistic formulation takes into account intensity and texture distributions in a local area around each region. It further incorporates priors based on the geometry of the regions. Finally, posteriors based on intensity and texture cues are combined using “ a mixture of experts” formulation. This probabilistic approach is integrated into a graph coarsening scheme, providing a complete hierarchical segmentation of the image. The algorithm complexity is linear in the number of the image pixels and it requires almost no user-tuned parameters. In addition, we provide a novel evaluation scheme for image segmentation algorithms, attempting to avoid human semantic considerations that are out of scope for segmentation algorithms. Using this novel evaluation scheme, we test our method and provide a comparison to several existing segmentation algorithms.

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Index Terms:
image texture,computational complexity,computer vision,graph theory,image segmentation,computer vision,probabilistic bottom-up aggregation,cue integration,pixel merging,texture distributions,texture cues,graph coarsening scheme,hierarchical image segmentation,algorithm complexity,user-tuned parameters,Image segmentation,Computer vision,Algorithm design and analysis,Probabilistic logic,Noise measurement,Partitioning algorithms,Clustering algorithms,segmentation evaluation.,Computer vision,image segmentation,cue integration
Citation:
S. Alpert, M. Galun, A. Brandt, R. Basri, "Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 2, pp. 315-327, Feb. 2012, doi:10.1109/TPAMI.2011.130
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